# Small Quiz (ungraded) [[quiz1]] 

Up to this point you have understood the big picture of Agents, what they are and how they work. It's time to make a short quiz, since **testing yourself** is the best way to learn and [to avoid the illusion of competence](https://www.coursera.org/lecture/learning-how-to-learn/illusions-of-competence-BuFzf). This will help you find **where you need to reinforce your knowledge**.

This is an optional quiz and it's not graded.

### Q1: What is an Agent?
Which of the following best describes an AI Agent?

<Question
choices={[
{
text: "A system that only processes static text and never interacts with its environment.",
explain: "An Agent must be able to take an action and interact with its environment.",
},
{
text: "An AI model that can reason, plan, and use tools to interact with its environment to achieve a specific goal.",
explain: "This definition captures the essential characteristics of an Agent.",
correct: true
},
{
text: "A chatbot that answers questions without any ability to perform actions.",
explain: "A chatbot like this lacks the ability to take actions, making it different from an Agent.",
},
{
text: "A digital encyclopedia that provides information but cannot perform tasks.",
explain: "An Agent actively interacts with its environment rather than just providing static information.",
}
]}
/>

---

### Q2: What is the Role of Planning in an Agent?
Why does an Agent need to plan before taking an action?

<Question
choices={[
{
text: "To memorize previous interactions.",
explain: "Planning is about determining future actions, not storing past interactions.",
},
{
text: "To decide on the sequence of actions and select appropriate tools needed to fulfill the user’s request.",
explain: "Planning helps the Agent determine the best steps and tools to complete a task.",
correct: true
},
{
text: "To generate random actions without any purpose.",
explain: "Planning ensures the Agent's actions are intentional and not random.",
},
{
text: "To translate text without any additional reasoning.",
explain: "Planning is about structuring actions, not just converting text.",
}
]}
/>

---

### Q3: How Do Tools Enhance an Agent's Capabilities?
Why are tools essential for an Agent?

<Question
choices={[
{
text: "Tools are redundant components that do not affect the Agent’s performance.",
explain: "Tools expand an Agent's capabilities by allowing it to perform actions beyond text generation.",
},
{
text: "Tools provide the Agent with the ability to execute actions a text-generation model cannot perform natively, such as making coffee or generating images.",
explain: "Tools enable Agents to interact with the real world and complete tasks.",
correct: true
},
{
text: "Tools are used solely for storing memory.",
explain: "Tools are primarily for performing actions, not just for storing data.",
},
{
text: "Tools limit the Agent to only text-based responses.",
explain: "On the contrary, tools allow Agents to go beyond text-based responses.",
}
]}
/>

---

### Q4: How Do Actions Differ from Tools?
What is the key difference between Actions and Tools?

<Question
choices={[
{
text: "Actions are the steps the Agent takes, while Tools are external resources the Agent can use to perform those actions.",
explain: "Actions are higher-level objectives, while Tools are specific functions the Agent can call upon.",
correct: true
},
{
text: "Actions and Tools are the same thing and can be used interchangeably.",
explain: "No, Actions are goals or tasks, while Tools are specific utilities the Agent uses to achieve them.",
},
{
text: "Tools are general, while Actions are only for physical interactions.",
explain: "Not necessarily. Actions can involve both digital and physical tasks.",
},
{
text: "Actions require LLMs, while Tools do not.",
explain: "While LLMs help decide Actions, Actions themselves are not dependent on LLMs.",
}
]}
/>

---

### Q5: What Role Do Large Language Models (LLMs) Play in Agents?
How do LLMs contribute to an Agent’s functionality?

<Question
choices={[
{
text: "LLMs are used as static databases that store information without processing input.",
explain: "LLMs actively process text input and generate responses, rather than just storing information.",
},
{
text: "LLMs serve as the reasoning 'brain' of the Agent, processing text inputs to understand instructions and plan actions.",
explain: "LLMs enable the Agent to interpret, plan, and decide on the next steps.",
correct: true
},
{
text: "LLMs are only used for image processing and not for text.",
explain: "LLMs primarily work with text, although they can sometimes interact with multimodal inputs.",
},
{
text: "LLMs are not used.",
explain: "LLMs are a core component of modern AI Agents.",
}
]}
/>

---

### Q6: Which of the Following Best Demonstrates an AI Agent?
Which real-world example best illustrates an AI Agent at work?

<Question
choices={[
{
text: "A static FAQ page on a website.",
explain: "A static FAQ page does not interact dynamically with users or take actions.",
},
{
text: "A virtual assistant like Siri or Alexa that can understand spoken commands, reason through them, and perform tasks like setting reminders or sending messages.",
explain: "This example includes reasoning, planning, and interaction with the environment.",
correct: true
},
{
text: "A basic calculator that performs arithmetic operations.",
explain: "A calculator follows fixed rules without reasoning or planning, so it is not an Agent.",
},
{
text: "A video game NPC that follows a scripted set of responses.",
explain: "Unless the NPC can reason, plan, and use tools, it does not function as an AI Agent.",
}
]}
/>

---

Congrats on finishing this Quiz 🥳, if you missed some elements, take time to read again the chapter to reinforce your knowledge. If you pass it, you're ready to dive deeper into the "Agent's brain": LLMs.
